Butyrate, a physiologically active molecule, can be synthesized through metabolic interactions among colonic microorganisms. Previously, in a fermenting trial of human fecal microbiota, we observed that the butyrogenic effect positively correlated with the increasing Bifidobacterium population and an unidentified Megasphaera species. Therefore, we hypothesized that a cross-feeding phenomenon exists between Bifidobacterium and Megasphaera , where Megasphaera is the butyrate producer, and its growth relies on the metabolites generated by Bifidobacterium . To validate this hypothesis, three bacterial species ( B. longum , B. pseudocatenulatum , and M. indica ) were isolated from fecal cultures fermenting hydrolyzed xylan; pairwise cocultures were conducted between the Bifidobacterium and M. indica isolates; the microbial interactions were determined based on bacterial genome information, cell growth, substrate consumption, metabolite quantification, and metatranscriptomics. The results indicated that two Bifidobacterium isolates contained distinct gene clusters for xylan utilization and expressed varying substrate preferences. In contrast, M. indica alone scarcely grew on the xylose-based substrates. The growth of M. indica was significantly elevated by coculturing it with bifidobacteria, while the two Bifidobacterium species responded differently in the kinetics of cell growth and substrate consumption. Coculturing led to the depletion of lactate and increased the formation of butyrate. An RNA-seq analysis further revealed the upregulation of M. indica genes involved in the lactate utilization and butyrate formation pathways. We concluded that lactate generated by Bifidobacterium through catabolizing xylose fueled the growth of M. indica and triggered the synthesis of butyrate. Our findings demonstrated a novel cross-feeding mechanism to generate butyrate in the human colon. IMPORTANCE: Butyrate is an important short-chain fatty acid that is produced in the human colon through microbial fermentation. Although many butyrate-producing bacteria exhibit a limited capacity to degrade nondigestible food materials, butyrate can be formed through cross-feeding microbial metabolites, such as acetate or lactate. Previously, the literature has explicated the butyrate-forming links between Bifidobacterium and Faecalibacterium prausnitzii and between Bifidobacterium and Eubacterium rectale . In this study, we provided an alternative butyrate synthetic pathway through the interaction between Bifidobacterium and Megasphaera indica. M. indica is a species named in 2014 and is indigenous to the human intestinal tract. Scientific studies explaining the function of M. indica in the human colon are still limited. Our results show that M. indica proliferated based on the lactate generated by bifidobacteria and produced butyrate as its end metabolic product. The pathways identified here may contribute to understanding butyrate formation in the gut microbiota.

We describe a novel collaboration between academia and industry, an in-house data science and artificial intelligence challenge held by Novartis to develop machine-learning models for predicting drug-development outcomes, building upon research at MIT using data from Informa as the starting point. With over 50 cross-functional teams from 25 Novartis offices around the world participating in the challenge, the domain expertise of these Novartis researchers was leveraged to create predictive models with greater sophistication. Ultimately, two winning teams developed models that outperformed the baseline MIT model—areas under the curve of 0.88 and 0.84 versus 0.78, respectively—through state-of-the-art machine-learning algorithms and the use of newly incorporated features and data. In addition to validating the variables shown to be associated with drug approval in the earlier MIT study, the challenge also provided new insights into the drivers of drug-development success and failure.

Background: The fast-spreading of Extended-Spectrum Beta-Lactamase-Producing Escherichia coli (ESBL-producing E. coli) and ESBL genes has become a big challenge to public health. The risk of spreading ESBL genes and pathogens in the environment and community has raised public health concern. The characterizing and whole-genome sequencing studies of ESBL-producing bacteria from reservoir water in Singapore is still limited. Materials and methods: The reservoir water sample was taken from two randomly selected sampling points of the Chinese Garden (Jurong river reservoir), which is a popular reservoir park in Singapore. The bacteria of the water sample were collected with 0.45 µm filter membranes and enriched before processing with ESBL-producing E. coli screening. The collected ESBL positive isolates were further characterized by both phenotypic tests including disc diffusion and microdilution Minimum Inhibitory Concentration (MIC) test, and also genotypic test as whole-genome sequencing analysis. Besides, to investigate the transferability of the resistance gene, a conjugation test was performed with the J53 E. coli strain as the gene receptor. Result: Nine ESBL-producing E. coli isolates were collected and confirmed as ESBL-producing with both phenotypic and genotypic tests. A potential pathogen as ST131 clade A isolate was identified, and all isolates were determined to harbor a bla_CTX-M gene. Among them, strain J1E4 was resistant to polymyxin E and confirmed to harboring a conjugatable mcr-1 gene. Further genetic environment analysis has reflected a conversed gene cluster formed by insert sequence (IS), bla_CTX-M-15, and WbuC family cupin-fold metalloprotein, which may potentially jump from the plasmids to the chromosome. Conclusion: The first time we reported the whole genome sequencing (WGS) data of ESBL-producing E. coli including potential pathogen (ST131) present in reservoir water in Singapore. The ESBL-producing E. coli from reservoir water also carrying conjugatable colistin resistance genes which may become a risk to human health.

Escherichia coli ST410, where the lineage is similar to the global pandemic ESBL E. coli lineage ST131, is emerging as new international high-risk clones.¹ It is an extraintestinal pathogen associated with resistance to fluoroquinolones, third-generation cephalosporins and carbapenems. Equipped with enhanced pathogenicity, E. coli ST410 can cause severe and/or recurrent infections, including patient-to-patient transmission causing hospital outbreaks.² While it has been reported that in Asia carbapenem-resistant E. coli ST410 was isolated as the causative pathogen of infections in patients of Sichuan hospitals in China and in Singapore,^2,3 there is no report of this carbapenem-resistant E. coli ST410 arising from the natural water environment in Asia, which is an important aspect in the One Health perspective. The One Health perspective recognizes that the health of humans, domestic and wild animals, plants and the wider environment (including ecosystems) are closely linked and interdependent, and collaborative effort is needed to attain optimal health for all sectors. To this end, we have found a carbapenem resistant E. coli ST410 strain SrichA-1 with a bla_NDM-5-bearing plasmid pSGNDM-5, isolated from reservoir water in Singapore (BioSample accession: SAMN18579051; SRA: SRP313016). A circular plasmid map of pSGNDM-5 was obtained by long-read next-generation sequencing (PacBio RS II) and a deep genetic investigation was applied.

Vibrio parahaemolyticus, commonly found in seafood products, is responsible for gastroenteritis resulting from the consumption of undercooked seafood. Hence, there is a need to characterize and quantify the risk involved from this pathogen. However, there has been no study reporting the quantification of hemolytic antimicrobial-resistant (AMR) Vibrio parahaemolyticus in locally farmed shellfish in Singapore. In this study, ampicillin, penicillin G, tetracycline resistant, and non-AMR hemolytic V. parahaemolyticus were surveyed and quantified in green mussel samples from different premises in the food chain (farm and retail). The occurrence data showed that 31/45 (68.9%) of farmed green mussel samples, 6/6 (100%) farm water samples, and 41/45 (91.1%) retail shellfish samples detected the presence of hemolytic V. parahaemolyticus. V. parahaemolyticus counts ranged from 1.6–5.9 Log CFU/g in the retail shellfish samples and 1.0–2.9 Log CFU/g in the farm water samples. AMR risk assessments (ARRA), specifically for ampicillin, penicillin G, tetracycline, and hemolytic (non-AMR) scenarios were conducted for the full farm-to-home and partial retail-to-home chains. The hemolytic ARRA scenario estimated an average probability of illness of 5.7 × 10⁻³ and 1.2 × 10⁻² per serving for the full and partial chains, respectively, translating to 165 and 355 annual cases per total population or 2.9 and 6.2 cases per 100,000 population, respectively. The average probability of illness per year ratios for the three ARRAs to the hemolytic ARRA were 0.82, 0.81, and 0.47 (ampicillin, penicillin G, and tetracycline, respectively) for the full chain and 0.54, 0.39, and 0.09 (ampicillin, penicillin G, and tetracycline, respectively) for the partial chain. The sensitivity analysis showed that the overall cooking effect, initial concentrations of pathogenic V. parahaemolyticus, and harvest duration and harvest temperature were key variables influencing the risk estimates in all of the modelled ARRAs. The study findings can be used by relevant stakeholders to make informed decisions for risk management that improve food safety.